درخت حوزه‌های تخصصی

The purpose of this research is to provide a model for reporting quality of financial information based on behavioral and value accounting of listed companies in Tehran Stock Exchange which is based on Structural Equation Modeling. This research in terms of applied purpose is applied research and in terms of data collection method is post-semi experimental research in the field of proofing accounting research with deductive- inductive approach. The statistical population of this is including the sample of 128 listed companies in the Tehran Stock Exchange between 2007 and 2017. The behavioral characteristics of managers (hidden variables) is measured by observable variables of myopia, opportunistic behavior and over confidence of managers and the value content of accounting information (hidden variable) is evaluated by the observable variables of relevance of profit and relevance of book value. And reporting quality of financial information is also investigated based on the scores accrued to each company and the announcement published by the Tehran Stock Exchange based on the companies' rating in terms of the quality of reporting and proper notification. After insuring the acceptable fitness of the measurement pattern and the structure of research in both approaches; Structural Equations Modeling and regression, the results indicate that there is a significant negative relationship between the behavioral characteristics of managers and the reporting quality financial information. Also, there is a positive and significant relationship between value content of accounting information and reporting quality of financial information.

Organizational risk is often defined as a change in the flow of profit, or as a sys-tematic or non-systematic changes in the stock return flow. The risk taking of management is conceptualized as the actual investment decisions that are indictors due to uncertainty results. The purpose of this study is to investigate the effect of financial characteristics on future corporate risk taking behavior. After designing the indicators for assessing financial characteristics, the transaction data were collected from the Stock Exchange in the five-year period of 2011-2015. A sample of 111 companies was selected by sampling method based on the Cochran formula, which resulted in a total of 555 year-firm observations. In this study, linear regression and correlation were used to investigate the hypothesis, and for analyzing data and hypothesis testing, we used Eviews software. What can be said in the summing-up and conclusion of the general test of research hypotheses is that the disproportionate changes in sales costs, advertising costs, rental costs, liquidity, financial leverage, and disproportionate changes in capital costs have a positive impact on future corporate risk taking behavior. In addition, other results indicate a negative impact of disproportionate changes in sales growth, inventory, liquidity, and asset turnover on future corporate risk-taking behavior. The results obtained in this paper are consistent with the documentation referenced in the research's theoretical framework and financial literature..

Technical analysis is one of the financial market analysis tools. Technical analysis is a method of anticipating prices and markets through studying historical market data. Based on the factors studied in this type of analysis, indicators are designed and presented to facilitate decision-making on buy and sell stress and then buy and sell action in financial markets. This research evaluates performances and returns of 10 conventional technical analysis indicators based on the strategies set on the total stock exchange index, the total index of OTC market and 8 other (non-correlated) industry indices by using Meta Trader software from 2008 to 2018. Also, the significance of the difference between the returns of the indicators is tested using the buy and hold strategy. The results show a significant difference between the returns using some of the technical analysis indicators in some indices and buy and hold strategy. The effectiveness of technical analysis strategies varies across industries and EMA and SMA with respectively 6 and 5 repetitions, are the best strategies and BB with just one repetition has the least repetition. The investment industry index with the most repetition is the industry in which the strategies used in this study have been able to provide an acceptable return.